First principle (ab initio) quantum chemistry methods are widely used for computational studies in biology, chemistry and material science. Among the various quantum chemistry models, density functional theory (DFT) offers a good balance between computational cost and accuracy and accordingly is the most widely used method in many scientific fields, including biological research. However, despite the remarkable advances in DFT in the past decade, the application of DFT to treat large biological systems or molecular dynamics is still limited by computational cost. Accordingly, the goal of the research proposed here is to increase the efficiency of DFT calculations by several fold through the implementation of novel algorithms. There are two major time-consuming parts in a DFT calculation, namely computation of the Coulomb and the exchange-correlation (XC) contributions. In the Phase I of this project, we implemented the Fourier Transform Coulomb method for the evaluation of the Coulomb contribution, and developed a new algorithm called multiresolution XC (mrXC), for the evaluation of XC contribution to the DFT energy with local functionals. The results show that FTC accelerates Coulomb calculation by up to a factor of 4.5 over the most efficient Coulomb algorithms. The mrXC method speeds up the calculation of XC contribution by as much as a factor of 5. In the Phase II of the project, we will develop and implement FTC and mrXC for the most widely used components of DFT calculations, including energy and gradients with respect to nuclear motions for both ground and excited states. Efforts will also be made to further improve the efficiency. Formulism will also be developed at the level of general-gradient approximation, the mostly widely used type of DFT functional. In order to demonstrate the utility of DFT algorithms developed here, we will carry out a state-of-the-art computational study of the mechanism of light-induced structural change in bacteriorhodopsin. These improvements will significantly increase Q-Chem users? productivity and greatly extend the complexity of molecular systems that can be studied using DFT. Furthermore, it will bring DFT much closer to our goal of being able to replace the less accurate but computationally less demanding models currently used today in molecular dynamics or Monte Carlo simulations of proteins and other large molecular systems. This project aims to improve the efficiency of the density-functional theory (DFT) calculations. DFT is at the core of molecular modeling and is applied widely in biological research/development and in drug discovery. The improved DFT will significantly increase researchers' productivity and extend its application scope. [unreadable] [unreadable] [unreadable]